AI Agents Are Flooding Public Services - Build Your Spring Boot Defenses Before They Reach Your API

说明与用途

公共服务正面临“代理泛滥”，即合法用户提交由AI生成的高量请求，导致处理团队不堪重负。文章建议使用Bucket4j对每个已认证用户的提交进行限制，但指出这无法解决定性泛滥（例如一次发送一个巨大的文档）的问题。

问题

Public services and APIs are experiencing 'agentic flooding' where legitimate, authenticated users submit high-volume, high-complexity requests generated by AI agents, overwhelming processing teams without triggering traditional bot detection.

结果

The implementation of per-identity rate limiting with burst allowances effectively caps the number of submissions from a single authenticated user, preventing quantitative flooding. However, it does not address qualitative flooding (e.g., massive single requests), requiring additional defenses.

工作流

• Identify submission endpoints that accept free-form text through open channels.
• Implement per-identity rate limiting using Bucket4j to handle quantitative flooding.
• Configure a bucket with a burst allowance (e.g., 5 submissions) and a refill rate (e.g., 5 per hour).
• Apply the rate limiter at the submission endpoint, not globally.
• Return a 429 status with a Retry-After header for legitimate users who hit the limit.
• Implement additional defenses for qualitative flooding (e.g., content analysis, size limits).

证据

In 87 percent of cases, the flooding came from LLMs generating large amounts of sophisticated text, submitted by humans who navigated the rest of the process manually.

来源

A user submitting one four-thousand-page document per hour is perfectly rate-limit-compliant.

来源